using machine learning detect threats von continental academy press (5 Ergebnisse)

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Cyber-physical systems are increasingly ubiquitous in modern life, from smart homes to industrial control systems. However, these systems are also vulnerable to a range of threats, from hacking to sabotage. Using Machine Learning to Detect Threats in Cyber-Physical Systems offers a cutting-edge exploration of the latest machine learning techniques for detecting and mitigating these threats. By examining the intersection of machine learning and cybersecurity, the author reveals new possibilities for the detection and prevention of cyber-physical threats. Through a series of case studies and theoretical analyses, this book provides a comprehensive guide to the latest machine learning techniques for cyber-physical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Insider Threats offers a cutting-edge approach to identifying and mitigating the risks posed by insider threats in the digital age. This forward-thinking text explores the application of machine learning algorithms and techniques to detect anomalous behavior patterns, predict potential insider threats, and prevent data breaches. By examining the strengths and limitations of various machine learning models and techniques, this book provides a comprehensive guide to implementing effective insider threat detection systems and minimizing the risks associated with insider attacks. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Threats in Cyber-Physical Systems is a cutting-edge exploration of the potential applications of machine learning in the context of cyber-physical systems. By examining the complex relationships between machine learning, cybersecurity, and cyber-physical systems, this book highlights the unique challenges and opportunities presented by the application of machine learning to threat detection in these systems. From the development of predictive models to the integration of anomaly detection algorithms, this book covers a wide range of topics, providing a comprehensive understanding of the intricate relationships between machine learning, cybersecurity, and cyber-physical systems. By exploring the use of machine learning to detect threats in cyber-physical systems, readers will gain a deeper appreciation for the potential of this approach to revolutionize the way we protect these critical systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Insider Threats explores the innovative application of artificial intelligence techniques to identify malicious activities within organizations. This book examines how machine learning models can analyze vast amounts of data to uncover subtle behavioral anomalies indicative of insider threats. It emphasizes the importance of developing robust algorithms capable of adapting to evolving tactics used by malicious insiders. The content provides insights into the integration of AI with cybersecurity frameworks, enhancing the ability to preemptively detect and mitigate internal security breaches. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Using Machine Learning to Detect Threats in Cyber-Physical Systems examines how advanced algorithms can identify vulnerabilities and malicious activities within interconnected systems. The book covers various machine learning techniques tailored for real-time threat detection, emphasizing the importance of proactive security measures in critical infrastructure. It provides insights into developing resilient cyber-physical environments through intelligent monitoring and anomaly detection. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.